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(R2) Positions Postdoc Positions Application Deadline 12 Oct 2026 - 00:00 (UTC) Country France Type of Contract Temporary Job Status Full-time Hours Per Week 35 Offer Starting Date 1 Dec 2026 Is the job
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University of North Carolina at Chapel Hill | Chapel Hill, North Carolina | United States | 3 days ago
as well as for federally funded social and behavioral sciences research and development. Here at Carolina, our highly skilled postdocs play a vital role in our research enterprise and towards our
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proteomics, transcriptomics, collected from state-of-the-art microfluidic lymph node on-a-chip systems used to study infection initiation and immune response. The postdoc will be co-mentored by
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on astrophysical source populations and dark-matter signals, exploiting statistical correlations across datasets to break degeneracies that limit single-probe analyses. The framework will be validated on synthetic
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Join us at the National Centre of Excellence CHARMEC for an exciting and excellent PostDoc journey to investigate hybrid asset management on railways! About us Your workplace will be at the Division
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(R2) Positions Postdoc Positions Application Deadline 13 Oct 2026 - 14:00 (Europe/Madrid) Country Spain Type of Contract Temporary Job Status Full-time Is the job funded through the EU Research
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approaches to optimising deployed AI systems as human-machine teams. The postdoc will conduct research developing and evaluating methods at the frontier of trustworthy AI, validating them on real-world
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24 Sep 2026 Job Information Organisation/Company Asociatia Transylvanian Institute of Neuroscience Research Field All Researcher Profile First Stage Researcher (R1) Positions Postdoc Positions
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12 Sep 2026 Job Information Organisation/Company Umeå universitet stipendiemodul Department Umeå School of Business, Economics and Statistics Research Field Mathematics » Statistics Researcher
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processing influence the resulting quantitative data. What you’ll do Generate systematic proteomic datasets as part of a collaborative team effort Develop and apply statistical and quantitative approaches